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Finding Alphas: A Quantitative Approach to Building Trading Strategies by Igor Tulchinsky

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27 Alphas and WebSim™ Fundamentals

By the WebSimTeam

With the development of information technology, information processing, automatic trading, etc., the market is always close to 100% efficiency but is never at 100%. We seek to arbitrage profit from this inefficiency.

It is difficult to predict one stock’s future return. One stock error due to noisy data will not hurt the whole performance. The process of betting many stocks every day is called statistical arbitrage, which is what WebSim™ does.

Statistical arbitrages are also called alphas. A good statistical arbitrage model usually involves a large number of securities and may have short holding periods, with positive returns expected in the long run.

ALPHAS AND WEBSIM™

An alpha is a mathematical, predictive model of the performance of financial instruments (e.g. stocks, futures contracts, etc.) that can be simulated historically using WebSim™. This model is comprised of data (e.g. close price, open price, volume, etc.) and mathematical expressions (+/–, StdDev(x, n), regression, etc.).

WebSim™ is a web-based simulator of global financial markets that was created to explore alpha research. It will accept an alpha expression/Python code as input and will plot its PnL as its output. The input expression is evaluated for each financial instrument, every day (history dates), and a portfolio is constructed accordingly. WebSim™ invests in each financial instrument to the value of the expression. It either takes a long or short ...

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